Abstract: Systems and methods are provided herein for creating and building a model of a unique infrastructure, such as a parking structure. The model may be created through the identification of various triggers by a vehicle traversing the infrastructure. The triggers may include, for example, sensors or other devices capable of sensing the vehicle within the infrastructure. The triggers may also be information received from the vehicle itself. Based on the triggers, it may be inferred that various places exist throughout the infrastructure. For example, it may be inferred through two subsequent triggers that a place exists between the two triggers. The place may be added to the model of the infrastructure in between the two triggers. The model may continue to grow in this manner.

Abstract: An audio sample including speech and ambient sounds is transmitted to a vehicle computer. Recorded audio is received from the vehicle computer, the recorded audio including the audio sample broadcast by the vehicle computer and recorded by the vehicle computer and recognized speech from the recorded audio. The recognized speech and text of the speech are input to a machine learning program that outputs whether the recognized speech matches the text. When the output from the machine learning program indicates that the recognized speech does not match the text, the recognized speech and the text are included in a training dataset for the machine learning program.

Abstract: A system includes a computer on board a vehicle and a server remote from the vehicle. The computer and the server each store a network graph of actions performable by components of the vehicle that includes costs of transitioning between the actions. The computer is programmed to log a sequence of the actions; upon determining that a sub-sequence of the sequence constitutes a lowest-cost path from the beginning action to the final action based on the network graph, store a reduced sequence including a beginning action and a final action of the sub-sequence ordered immediately after the beginning action, the reduced sequence excluding at least one intermediate action from the sub-sequence; and transmit the reduced sequence to a server remote from the vehicle. The server is programmed to determine the sequence from the reduced sequence based on the network graph.

Abstract: Managing data transfer and privacy via a multi-channel transfer of information is provided. A query is received from a client device, the query indicating an access identifier corresponding to an entity for which data is stored. A consented data pool is accessed to identify a random value corresponding to the access identifier. A hash value is computed using a combination of both the access identifier and the random value. An anonymous data pool of stored data is queried to identify results from the stored data tagged with the hash value. The results are returned to the client device responsive to the query.

Abstract: An audio sample including speech and ambient sounds is transmitted to a vehicle computer. Recorded audio is received from the vehicle computer, the recorded audio including the audio sample broadcast by the vehicle computer and recorded by the vehicle computer and recognized speech from the recorded audio. The recognized speech and text of the speech are input to a machine learning program that outputs whether the recognized speech matches the text. When the output from the machine learning program indicates that the recognized speech does not match the text, the recognized speech and the text are included in a training dataset for the machine learning program.

Abstract: Methods and systems for vehicle localization are provided herein. An example method can include obtaining a map within an operating area. A location within the operating area is associated with a pattern of speed bumps that is configured to produce a vehicle pitch response from the vehicle when the vehicle travels over the pattern of speed bumps. The method can include obtaining motion sensor information from a vehicle sensor, determining when the motion sensor information matches the vehicle pitch response, and determining that the vehicle is in the location when the motion sensor information corresponds to the vehicle pitch response of the location.

Abstract: Vehicle-based sign language communication systems and methods are provided herein. An example device can be configured to determine a sign language protocol used by the first user, determine a target language used by a second user, obtain a translation library based on the sign language protocol and the target language, receive spoken word input from a second user through a microphone, convert the spoken word input into sign language output using the translation library, and provide the sign language output using a sign language output device.

Abstract: Systems and methods are provided herein for creating and building a model of a unique infrastructure, such as a parking structure. The model may be created through the identification of various triggers by a vehicle traversing the infrastructure. The triggers may include, for example, sensors or other devices capable of sensing the vehicle within the infrastructure. The triggers may also be information received from the vehicle itself. Based on the triggers, it may be inferred that various places exist throughout the infrastructure. For example, it may be inferred through two subsequent triggers that a place exists between the two triggers. The place may be added to the model of the infrastructure in between the two triggers. The model may continue to grow in this manner.

Abstract: Methods and systems for vehicle localization are provided herein. An example method can include obtaining a map within an operating area. A location within the operating area is associated with a pattern of speed bumps that is configured to produce a vehicle pitch response from the vehicle when the vehicle travels over the pattern of speed bumps. The method can include obtaining motion sensor information from a vehicle sensor, determining when the motion sensor information matches the vehicle pitch response, and determining that the vehicle is in the location when the motion sensor information corresponds to the vehicle pitch response of the location.

Abstract: Systems and methods are disclosed for an embedded in-vehicle platform that provides immersive user experiences. An example method includes obtaining, by a vehicle controller of a vehicle, a preference profile for a user; loading the preference profile by the vehicle controller; determining a shopping experience of the user occurring on a vehicle shopping platform within the vehicle; determining an ambience profile of a merchant identified in the shopping experience; and controlling, by the vehicle controller, an in-vehicle ambience within the vehicle based on the ambience profile and the preference profile.

Abstract: Vehicle-based sign language communication systems and methods are provided herein. An example device can be configured to determine a sign language protocol used by the first user, determine a target language used by a second user, obtain a translation library based on the sign language protocol and the target language, receive spoken word input from a second user through a microphone, convert the spoken word input into sign language output using the translation library, and provide the sign language output using a sign language output device.

Abstract: Riders may request rides from a rider location to a desired destination. Possible stops are selected according to a fairness calculation that accounts for distance, weather, and wait times. Stops may be selected from among predefined virtual stops and based on virtual curb colors defining permitted stopping locations. Stops may be moved to promotional locations or to avoid stop congestion due to too many shuttles or too many riders using the stop. Routes are calculated for these stops and ETAs for the routes calculated based on traffic congestion data. Stop locations are communicated to riders and updated based on current traffic conditions or change in rider locations.

Abstract: Systems and methods are disclosed for an embedded in-vehicle platform that provides immersive user experiences. An example method includes obtaining, by a vehicle controller of a vehicle, a preference profile for a user; loading the preference profile by the vehicle controller; determining a shopping experience of the user occurring on a vehicle shopping platform within the vehicle; determining an ambience profile of a merchant identified in the shopping experience; and controlling, by the vehicle controller, an in-vehicle ambience within the vehicle based on the ambience profile and the preference profile.